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Last year at this meeting we described a computer application (Brown and Storrie-Lombardi, 2006),
the Mars Reconnaissance PRISM or MR PRISM, designed to analyze hyperspectral data collected
by the Compact Imaging Spectrometer for Mars (CRISM). The application links the spectral,
imaging and mapping perspectives on the CRISM dataset by presenting the user with three different
ways to analyze the data. At this time last year, CRISM was still in calibration mode and we
presented data from ESA's OMEGA instrument to demonstrate the functionality of MR CRISM.
A primary goal in developing this application is to make the latest algorithms for detection of
spectrally interesting targets available to the Planetary Science community without cost to the
individual investigator and with a minimal learning barrier. This would enable the community to
look for Mars surface targets such as ices, hydrothermal minerals, sulfate minerals and hydrous
minerals and map the extent of these deposits. The CRISM team has now provided significant data
sets to our community. We have used one such data set to conduct a study on an exposed water ice
mound. We review here our results on observations made of a ~36km diameter crater, recently
named Louth, in the north polar region of Mars (at 70°N, 103.2°E). High-resolution imagery from
the instruments on the Mars Reconnaissance Orbiter spacecraft were used to map a 15km diameter
water ice deposit in the center of the crater. The water ice mound has surface features that include
roughened ice textures and layering similar to that found in the North Polar Layered Deposits. We
describe the data analysis process including detection and mapping of hydroxyl mineral signatures
using the MR PRISM software suite.
MR PRISM is currently in the prototyping stage. Future additions planned include a Bayesian
analysis engine, the capacity to handle atmospheric correction routines provided by the CRISM
team, the ability to display MOC, THEMIS and HiRISE data and eventually the ability to run on a
distributed network to speed up processing of large image cubes. When the software is released to
the general community, we hope its embedded scripting language, 'Groovy', will make it the 'front
end' for many more sophisticated algorithms from all branches of Mars research.
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